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Month 1 23 4 5 6 Value 26 15 22 14 21 25 17 (a) Construct a time series plot. 30 30 30 20 15 15 10 10 10 10 1 2 3 4 s 3 45 6 1 4. 1 1 Month Month Month Month What type of pattern exists in the data? O The data appear to follow a seasonal pattern. O The data appear to follow a cyclical pattern. O The data appear to follow a horizontal pattern. O The data appear to follow a trend pattern. (b) Develop the three-month moving average forecasts for this time series. Time Series Value Month Forecast 1 26 2 15 3 22 4 14 21 6 25 17

Month 1 23 4 5 6 Value 26 15 22 14 21 25 17 (a) Construct a time series plot. 30 30 30 20 15 15 10 10 10 10 1 2 3 4 s 3 45 6 1 4. 1 1 Month Month Month Month What type of pattern exists in the data? O The data appear to follow a seasonal pattern. O The data appear to follow a cyclical pattern. O The data appear to follow a horizontal pattern. O The data appear to follow a trend pattern. (b) Develop the three-month moving average forecasts for this time series. Time Series Value Month Forecast 1 26 2 15 3 22 4 14 21 6 25 17

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Consider the following time series data. Month 1 2 4 Value 26 15 22 14| 21 25 17 (a) Construct a time series plot. 30- 30 30 т 30 25 25 25 20 20 15- 10- 10- 10- 5- 1 2 4 5 6 7. 8. 1 2 3 4 6 8 1 3 4 6 8 1 3 4 6 8 Month Month Month Month What type of pattern exists in the data? O The data appear to follow a seasonal pattern. O The data appear to follow a cyclical pattern. O The data appear to follow a horizontal pattern. O The data appear to follow a trend pattern. (b) Develop the three-month moving average forecasts for this time series. Time Series Value Month Forecast 1 26 2 15 3 22 4 14 21 25 7 17 Time Series Value
Transcribed Image Text:Consider the following time series data. Month 1 2 4 Value 26 15 22 14| 21 25 17 (a) Construct a time series plot. 30- 30 30 т 30 25 25 25 20 20 15- 10- 10- 10- 5- 1 2 4 5 6 7. 8. 1 2 3 4 6 8 1 3 4 6 8 1 3 4 6 8 Month Month Month Month What type of pattern exists in the data? O The data appear to follow a seasonal pattern. O The data appear to follow a cyclical pattern. O The data appear to follow a horizontal pattern. O The data appear to follow a trend pattern. (b) Develop the three-month moving average forecasts for this time series. Time Series Value Month Forecast 1 26 2 15 3 22 4 14 21 25 7 17 Time Series Value
Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for month 8? (c) Use a = 0.2 to compute the exponential smoothing forecasts for the time series. (Round your answers to two decimal places.) Time Series Value Month Forecast 1 26 15 3 22 4 14 21 25 7 17 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for month 8? (Round your answer to two decimal places.) (d) Compare the three-month moving average approach with the exponential smoothing approach using a = 0.2. Which appears to provide more accurate forecasts based on MSE? O The three-month moving average provides a better forecast since it has a larger MSE than the exponential smoothing using a = 0.2. O The exponential smoothing using a = 0.2 provides a better forecast since it has a larger MSE than the three-month moving average. O The exponential smoothing using a = 0.2 provides a better forecast since it has a smaller MSE than the three-month moving average. O The three-month moving average provides a better forecast since it has a smaller MSE than the exponential smoothing using a = 0.2.
Transcribed Image Text:Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for month 8? (c) Use a = 0.2 to compute the exponential smoothing forecasts for the time series. (Round your answers to two decimal places.) Time Series Value Month Forecast 1 26 15 3 22 4 14 21 25 7 17 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for month 8? (Round your answer to two decimal places.) (d) Compare the three-month moving average approach with the exponential smoothing approach using a = 0.2. Which appears to provide more accurate forecasts based on MSE? O The three-month moving average provides a better forecast since it has a larger MSE than the exponential smoothing using a = 0.2. O The exponential smoothing using a = 0.2 provides a better forecast since it has a larger MSE than the three-month moving average. O The exponential smoothing using a = 0.2 provides a better forecast since it has a smaller MSE than the three-month moving average. O The three-month moving average provides a better forecast since it has a smaller MSE than the exponential smoothing using a = 0.2.
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